Direct Adaptive Control of Faulty UAVs via Quantum Feedforward and Fuzzy Feedback

Abstract:

In this paper, the control law designing of longitudinal-lateral attitude and faults self-repairing against the UAVs are analyzed. The direct adaptive controller via fuzzy feedback is designed to guarantee the UAVs stabe and having good flying performance. Then, a new direct adaptive control method is formulated by quantum control technique. Consequently, not only the stable error but the property of response and robustness is improved well. Simulation results are given to illustrate that a good dynamic performance of the flight control system with large faults can be maintained with the proposed control method.

• Periodical: Applied Mechanics and Materials (Volumes 130-134)
• Pages: 1973-1977
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.130-134.1973
• Online since: October 2011
• Authors: Fu Yang Chen, Bin Jiang, Changan Jiang
• Keywords: Adaptive Control, Fuzzy Feedback, Quantum Control Techniques, Self-Repairing Control, UAVs

References

[1] L. Li, F.C. Sun, Y. N. Hu. Adaptive fuzzy control approach for UAV flight control [J]. Electronics Optics & Control, vol. 14, No. 5, pp.117-123, (2007).

[2] C. Zhao, C.Y. Wen. Exploration on comprehensive effectiveness of a campaign system [J]. Electronics Optics & Control, vol. 8, No. 1, pp.63-65, (2001).

[3] X.M. Li, A. Zhang , J.G. Shi. Loss evaluation model of group airplanes attacking around targets [J]. Flight Dynamics, vol. 22, No. 2, pp.24-40, (2004).

[4] X.H. Qi, Z.J. Yang, X.B. Wu. Survey study of self -repairing flight control system on UAV [J]. Control Engineering of China, vol. 13, No. 6, pp.513-516, (2006).

[5] Z.H. Chen, D.Y. Dong, C.B. Zhang. Quantum Control Theory [M]. Hefei: University of Science and Technology of China Press, (2005).

[6] S. Cong. Quantum System Control Survey of Progress in Quantum Control System [J]. Chinese Journal of Quantum Electronica, vol. 20, No. 1, pp.1-9, (2003).

[7] K.H. Han & J.H. Kim. Genetic quantum algorithm and its application to combinational optimization problem [C]. /Proceedings of the International Congress on Evolutionary Computation. IEEE Press, pp.1354-1360.

[8] S.Y. Li & P.C. Li. Quantum computation and Quantum Optimization Algorithms[M]. Harbin: Harbin Institute of Technology Press, (2009).

[9] D.Y. Dong, C.L. Chen, etc. Incoherent Control of Quantum Systems with Wavefunction Controllable Subspaces via Quantum Reinforcement Learning [J]. IEEE Transactions on Systems, Man, and Cybernetics. Vol. 38, No. 4, pp.957-962, (2008).

DOI: 10.1109/tsmcb.2008.926603

[10] D.Q. Feng, S.H. Xie. Fuzzy brainpower control [M]. Beijing: Chemical Industry Press, (1997).